药物发现和开发中的人工智能:提高每项决策的质量
Shota Furukawa1,2, Hiroyuki Uchida1, Taishiro Kishimoto3
1Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan.
Pharmacopsychiatry
|March 5, 2026
概括
药物发现中的人工智能 (AI) 加快了时间表并提高了化合物质量. 将人工智能与监管框架和各种数据集集集成,可以提高决策能力,减少开发效率低下.
科学领域:
- 药物的发现和开发.
- 医学中的人工智能
- 监管科学是一种监管科学.
背景情况:
- 药物研究面临诸多挑战,包括长时间,高成本和显著的消耗率.
- 人工智能 (AI) 的最新进展为这些挑战提供了潜在的解决方案.
- 全球监管框架正在不断发展,以适应人工智能驱动的创新.
研究的目的:
- 审查近期AI在药物发现和开发方面的进展.
- 将人工智能创新与全球监管框架保持一致.
- 探索AI如何增强决策和减少药物研发中的低效率.
主要方法:
- 在药物开发管道中整合最近人工智能进步的叙事审查.
- 在目标识别,药物重定向,分子设计,结构生物学,安全预测和临床开发中分析AI应用.
- 检查人工智能与监管指南和新方法方法的整合.
主要成果:
- 人工智能集成可以缩短开发时间表,提高化合物质量,提高早期阶段的成功率.
- 预测和可解释的人工智能,结合机械先验和外部验证,增强决策.
- 案例研究表明,人工智能辅助的发现和重新定位具有好处,但过度匹配和数据集偏差等挑战仍然存在.
结论:
- 人工智能对优化药物研发具有重大前景.
- 建立信誉计划和确保设计时的公平性对于可概括的AI影响至关重要.
- 人工智能与新方法和适应性试验的整合可以在不妥协严格的情况下降低低效率.
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